Resource planning is a complicated process that relies heavily on the accuracy of the data available. Oftentimes the data that is received is not entirely accurate and may be off by a relatively small amount. However, those minute differences can propagate throughout an entire system and result in inefficiencies and wasted resources. As data from lower devices roll up to parent devices, data quality issues caused by incorrect configuration can cascade across an entire dataset. This can make planning changes and managing capacity a very complicated and manual process. Data centers are typically unable to calculate essentially how much electricity is used at a minute level. Information is usually only available at an aggregate level in the form of a bill from an electric company, for example. Although data for individual devices may be collected, there is no mechanism to identify the relationships between two different pieces of hardware on a data center floor.
Other drawbacks may also be present.